Short Bio
I am a PhD candidate in the School of Mathematics & Statistics, UNSW Sydney. I am supervised by Zdravko Botev and Sarat Moka.
My research focuses on sparse statistical learning in high-dimensional settings. My PhD has centred on developing optimisation methods for sparse statistical models, including scalable algorithms for convex ℓ₁-constrained problems using majorisation–minimisation techniques and for non-convex ℓ₀-constrained problems via binary relaxation methods. More broadly, I am interested in challenges arising in high-dimensional statistics and model compression.
My applied interests include developing algorithms and statistical methods for large-scale genomic data, particularly for genome-wide association studies (GWAS). I am also interested to adapt these and related computational techniques to risk management, transportation optimisation, and efficient pruning in deep learning.
Education
- PhD (Statistics) — UNSW Sydney, Sep 2020 ‑ (Expected) May 2025
- BSc (Hons). (Statistics) — UNSW Sydney, 2015‑2019